‘SIM-CITY’ granted

SIM-CITY will study and develop an agent-based complex network system to interactively explore socio-economic scenarios that can support decision makers of large urban areas, notably greater Amsterdam (de Randstad). The research will provide a decision support infrastructure for 2 case studies: Large-scale Evacuation Strategies in Case of Emergencies, and Dense City Infectious Diseases Pressure.

Catastrophes on the scale of the 2011 earthquake and tsunami in Japan are thankfully rare in the Netherlands. Over the past few years, however, we have seen various emergencies of one sort or another that still have a significant impact on our ability to go about our daily lives. It is crucial to have access to the right data and to have methods and tools to assess various scenarios of the possible development and extent of these disasters. The good news is that recent advances in experimental techniques have opened up new vistas into physical, biological and socio-economic processes on many levels of detail.

The ultimate goal of SIM-CITY is to develop a novel complex agent-based network (CAN) method to simulate, understand and manage complex, urban, socially interactive systems, with a focus on crisis management. We will build a prototype distributed decision support system that will allow for interactively exploring various scenarios of intervention. SIM-CITY will take data from for instance urban census data, demographic data, traffic and logistics to distill model parameters and provide support for ‘what-if’ CAN simulations to assist the city council in assessing intervening strategies.